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Ayala, A., S. Tomov, P. Luszczek, S. Cayrols, G. Ragghianti, and J. Dongarra, “Analysis of the Communication and Computation Cost of FFT Libraries towards Exascale,” ICL Technical Report, no. ICL-UT-22-07: Innovative Computing Laboratory, July 2022.  (5.91 MB)
Ayala, A., S. Tomov, M. Stoyanov, A. Haidar, and J. Dongarra, “Accelerating Multi - Process Communication for Parallel 3-D FFT,” 2021 Workshop on Exascale MPI (ExaMPI), St. Louis, MO, USA, IEEE, December 2021.
Ayala, A., S. Tomov, A. Haidar, and J. Dongarra, heFFTe: Highly Efficient FFT for Exascale (Poster) : NVIDIA GPU Technology Conference (GTC2020), October 2020.  (866.88 KB)
Ayala, A., S. Tomov, A. Haidar, M.. Stoyanov, S. Cayrols, J. Li, G. Bosilca, and J. Dongarra, Accelerating FFT towards Exascale Computing : NVIDIA GPU Technology Conference (GTC2021), 2021.  (27.23 MB)
Ayala, A., S. Tomov, X. Luo, H. Shaiek, A. Haidar, G. Bosilca, and J. Dongarra, “Impacts of Multi-GPU MPI Collective Communications on Large FFT Computation,” Workshop on Exascale MPI (ExaMPI) at SC19, Denver, CO, November 2019.  (1.6 MB)
Ayala, A., S. Tomov, P. Luszczek, S. Cayrols, G. Ragghianti, and J. Dongarra, “FFT Benchmark Performance Experiments on Systems Targeting Exascale,” ICL Technical Report, no. ICL-UT-22-02, March 2022.  (5.87 MB)
Ayala, A., S. Tomov, A. Haidar, and J. Dongarra, heFFTe: Highly Efficient FFT for Exascale (Poster) , Seattle, WA, SIAM Conference on Parallel Processing for Scientific Computing (SIAM PP20), February 2020.  (1.54 MB)
Ayala, A., S. Tomov, M. Stoyanov, and J. Dongarra, “Scalability Issues in FFT Computation,” International Conference on Parallel Computing Technologies: Springer, pp. 279–287, 2021.
Ayala, A., S. Tomov, A. Haidar, and J. Dongarra, “heFFTe: Highly Efficient FFT for Exascale,” International Conference on Computational Science (ICCS 2020), Amsterdam, Netherlands, June 2020.  (2.62 MB)
Ayala, A., S. Tomov, J. Dongarra, and A. Haidar, heFFTe: Highly Efficient FFT for Exascale (Poster) , Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.  (6.2 MB)
Ayala, A., S. Tomov, M. Stoyanov, A. Haidar, and J. Dongarra, “Performance Analysis of Parallel FFT on Large Multi-GPU Systems,” 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Lyon, France, IEEE, August 2022.
Ayala, A., S. Tomov, P. Luszczek, S. Cayrols, G. Ragghianti, and J. Dongarra, “Interim Report on Benchmarking FFT Libraries on High Performance Systems,” Innovative Computing Laboratory Technical Report, no. ICL-UT-21-03: University of Tennessee, July 2021.  (2.68 MB)
Aupy, G., A. Benoit, B. Goglin, L. Pottier, and Y. Robert, “Co-Scheduling HPC Workloads on Cache-Partitioned CMP Platforms,” Cluster 2018, Belfast, UK, IEEE Computer Society Press, September 2018.  (423.75 KB)
Aupy, G., A. Gainaru, V. Honoré, P. Raghavan, Y. Robert, and H. Sun, “Reservation Strategies for Stochastic Jobs,” 33rd IEEE International Parallel and Distributed Processing Symposium (IPDPS 2019), Rio de Janeiro, Brazil, IEEE Computer Society Press, May 2019.  (808.93 KB)
Aupy, G., A. Benoit, L. Pottier, P. Raghavan, Y. Robert, and M. Shantharam, “Co-Scheduling Algorithms for Cache-Partitioned Systems,” 19th Workshop on Advances in Parallel and Distributed Computational Models, Orlando, FL, IEEE Computer Society Press, May 2017.  (584.76 KB)
Aupy, G., A. Benoit, B. Goglin, L. Pottier, and Y. Robert, “Co-Scheduling HPC Workloads on Cache-Partitioned CMP Platforms,” International Journal of High Performance Computing Applications, vol. 33, issue 6, pp. 1221-1239, November 2019.  (930.28 KB)
Aupy, G., A. Benoit, S. Dai, L. Pottier, P. Raghavan, Y. Robert, and M. Shantharam, “Co-Scheduling Amdhal Applications on Cache-Partitioned Systems,” International Journal of High Performance Computing Applications, vol. 32, issue 1, pp. 123–138, January 2018.  (672.52 KB)
Aupy, G., A. Benoit, T. Herault, Y. Robert, and J. Dongarra, “Optimal Checkpointing Period: Time vs. Energy,” University of Tennessee Computer Science Technical Report (also LAWN 281), no. ut-eecs-13-718: University of Tennessee, October 2013.  (440.13 KB)
Aupy, G., and Y. Robert, “Scheduling for fault-tolerance: an introduction,” Innovative Computing Laboratory Technical Report, no. ICL-UT-15-02: University of Tennessee, January 2015.  (416.37 KB)
Aupy, G., and Y. Robert, “Scheduling for Fault-Tolerance: An Introduction,” Topics in Parallel and Distributed Computing: Springer International Publishing, pp. 143–170, 2018.
Aupy, G., A. Benoit, T. Herault, Y. Robert, F. Vivien, and D. Zaidouni, “On the Combination of Silent Error Detection and Checkpointing,” UT-CS-13-710: University of Tennessee Computer Science Technical Report, June 2013.  (1.29 MB)
Aupy, G., A. Benoit, H. Casanova, and Y. Robert, “Scheduling Computational Workflows on Failure-prone Platforms,” International Journal of Networking and Computing, vol. 6, no. 1, pp. 2-26, 2016.  (503.81 KB)
Aupy, G., M. Faverge, Y. Robert, J. Kurzak, P. Luszczek, and J. Dongarra, “Implementing a systolic algorithm for QR factorization on multicore clusters with PaRSEC,” Lawn 277, no. UT-CS-13-709, May 2013.  (298.63 KB)
Aupy, G., Y. Robert, and F. Vivien, “Assuming failure independence: are we right to be wrong?,” The 3rd International Workshop on Fault Tolerant Systems (FTS), Honolulu, Hawaii, IEEE, September 2017.  (597.11 KB)
Asch, M., T. Moore, R. M. Badia, M. Beck, P. Beckman, T. Bidot, F. Bodin, F. Cappello, A. Choudhary, B. R. de Supinski, et al., “Big Data and Extreme-Scale Computing: Pathways to Convergence - Toward a Shaping Strategy for a Future Software and Data Ecosystem for Scientific Inquiry,” The International Journal of High Performance Computing Applications, vol. 32, issue 4, pp. 435–479, July 2018.  (1.29 MB)
Arnold, D., S. Browne, J. Dongarra, G. Fagg, and K. Moore, “Secure Remote Access to Numerical Software and Computation Hardware,” University of Tennessee Computer Science Technical Report, UT-CS-00-446, July 2000.  (402.31 KB)
Arnold, D., S. Blackford, J. Dongarra, V. Eijkhout, and T. Xu, “Seamless Access to Adaptive Solver Algorithms,” Proceedings of 16th IMACS World Congress 2000 on Scientific Computing, Applications Mathematics and Simulation, Lausanne, Switzerland, August 2000.  (151.42 KB)
Arnold, D., S. Vadhiyar, and J. Dongarra, “On the Convergence of Computational and Data Grids,” Parallel Processing Letters, vol. 11, no. 2-3, pp. 187-202, January 2001.  (213.35 KB)
Arnold, D., W. Lee, J. Dongarra, and M. Wheeler, “Providing Infrastructure and Interface to High Performance Applications in a Distributed Setting,” ASTC-HPC 2000, Washington, DC, April 2000.  (96.04 KB)
Arnold, D., D. Bachmann, and J. Dongarra, “Request Sequencing: Optimizing Communication for the Grid,” Lecture Notes in Computer Science: Proceedings of 6th International Euro-Par Conference 2000, Parallel Processing, (Germany: Springer Verlag 2000), pp. V1900,1213-1222, January 2000.  (165.92 KB)
Arnold, D., and J. Dongarra, “The NetSolve Environment: Progressing Towards the Seamless Grid,” 2000 International Conference on Parallel Processing (ICPP-2000), Toronto, Canada, August 2000.  (148.85 KB)
Arnold, D., H. Casanova, and J. Dongarra, “Innovations of the NetSolve Grid Computing System,” Concurrency: Practice and Experience, vol. 14, no. 13-15, pp. 1457-1479, January 2002.  (311.31 KB)
Arnold, D., and J. Dongarra, “Developing an Architecture to Support the Implementation and Development of Scientific Computing Applications,” to appear in Proceedings of Working Conference 8: Software Architecture for Scientific Computing Applications, Ottawa, Canada, October 2000.  (176.25 KB)
Arnold, D., S. Browne, J. Dongarra, G. Fagg, and K. Moore, “Secure Remote Access to Numerical Software and Computational Hardware,” Proceedings of the DoD HPC Users Group Conference (HPCUG) 2000, Albuquerque, NM, June 2000.  (172.6 KB)
Archibald, R., E. Chow, E. D'Azevedo, J. Dongarra, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, S. Tomov, K. Wong, et al., “Integrating Deep Learning in Domain Sciences at Exascale,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-10: University of Tennessee, August 2020.  (1.09 MB)
Archibald, R., E. Chow, E. D'Azevedo, J. Dongarra, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, S. Tomov, K. Wong, et al., “Integrating Deep Learning in Domain Sciences at Exascale,” 2020 Smoky Mountains Computational Sciences and Engineering Conference (SMC 2020), August 2020.
Arbenz, P., A. Cleary, J. Dongarra, and M. Hegland, “A Comparison of Parallel Solvers for Diagonally Dominant and General Narrow Banded Linear Systems II (LAPACK Working Note 143),” University of Tennessee Computer Science Department Technical Report, no. UT-CS-99-415, January 1999.  (174.46 KB)
Arbenz, P., A. Cleary, J. Dongarra, and M. Hegland, “A Comparison of Parallel Solvers for General Narrow Banded Linear Systems,” Parallel and Distributed Computing Practices, vol. 2, pp. 385-400, October 2002.  (304.96 KB)
Arbenz, P., A. Cleary, J. Dongarra, and M. Hegland, “A Comparison of Parallel Solvers for General Narrow Banded Linear Systems (LAPACK Working Note 142),” University of Tennessee Computer Science Technical Report, no. UT-CS-99-414, January 1999.  (304.96 KB)
Anzt, H., S. Tomov, M. Gates, J. Dongarra, and V. Heuveline, Block-asynchronous Multigrid Smoothers for GPU-accelerated Systems , no. UT-CS-11-689, December 2011.  (608.95 KB)
Anzt, H., J. Dongarra, M. Kreutzer, G. Wellein, and M. Kohler, “Efficiency of General Krylov Methods on GPUs – An Experimental Study,” The Sixth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), Chicago, IL, IEEE, May 2016.  (285.28 KB)
Anzt, H., S. Tomov, and J. Dongarra, “On the performance and energy efficiency of sparse linear algebra on GPUs,” International Journal of High Performance Computing Applications, October 2016.  (1.19 MB)
Anzt, H., S. Tomov, and J. Dongarra, “Energy Efficiency and Performance Frontiers for Sparse Computations on GPU Supercomputers,” Sixth International Workshop on Programming Models and Applications for Multicores and Manycores (PMAM '15), San Francisco, CA, ACM, February 2015.  (2.29 MB)
Anzt, H., T. Huckle, J. Bräckle, and J. Dongarra, “Incomplete Sparse Approximate Inverses for Parallel Preconditioning,” Parallel Computing, vol. 71, pp. 1–22, January 2018.  (1.24 MB)
Anzt, H., S. Tomov, and J. Dongarra, “Accelerating the LOBPCG method on GPUs using a blocked Sparse Matrix Vector Product,” Spring Simulation Multi-Conference 2015 (SpringSim'15), Alexandria, VA, SCS, April 2015.  (1.46 MB)
Anzt, H., J. Dongarra, and V. Heuveline, “Weighted Block-Asynchronous Relaxation for GPU-Accelerated Systems,” SIAM Journal on Computing (submitted), March 2012.  (811.01 KB)
Anzt, H., E. Chow, J. Saak, and J. Dongarra, “Updating Incomplete Factorization Preconditioners for Model Order Reduction,” Numerical Algorithms, vol. 73, issue 3, no. 3, pp. 611–630, February 2016.  (565.34 KB)
Anzt, H., J. Dongarra, G. Flegar, and T. Gruetzmacher, “Variable-Size Batched Condition Number Calculation on GPUs,” SBAC-PAD, Lyon, France, September 2018.  (509.3 KB)
Anzt, H., D. Lukarski, S. Tomov, and J. Dongarra, “Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures,” VECPAR 2014, Eugene, OR, June 2014.  (430.56 KB)
Anzt, H., E. Chow, and J. Dongarra, “Iterative Sparse Triangular Solves for Preconditioning,” EuroPar 2015, Vienna, Austria, Springer Berlin, August 2015.  (322.36 KB)

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